26 to 50 of 995 Machine Learning Jobs in London

Joybuy combines speed, reliability, and affordability to meet the needs of modern shoppers. In this role, you will design, develop, and deploy AI/ML solutions that power Joybuy. You will work at the intersection of machine learning, engineering, and product, building intelligent systems that drive personalisation, search … recommendation, content understanding, and operational efficiency at scale. Key Responsibilities Design, build, and maintain AI/ML models and pipelines for Joybuy's international platform, covering areas such as personalisation, recommendation, NLP/LLM applications, computer vision, and fraud detection. Own end-to-end machine learning lifecycle from ...

About Machine Learning Platform Engineering at Monzo: The Platform Collective builds and maintains the infrastructure, tools and processes that set the rest of Monzo technology teams up for success. We work on a wide range of shared infrastructure, services and engineering tooling. The Machine Learning Platform … deploy, and serve Machine Learning models and features at scale. Our team is made up of backend engineers with experience in the ML space, using our experience and curiosity to work with the ML teams to identify their needs, and test and build simple solutions. Locations & Flexible Working ...

products, platforms, and operational environments. Responsibilities Define and guide machine learning strategy across multiple portfolio companies Help AI and engineering teams move ML initiatives from proof of concept into scalable production systems Align machine learning initiatives with product, commercial, and operational goals Advise on architecture across … operating models to improve execution maturity Qualifications 10+ years of experience across machine learning, AI, or data-driven environments Experience leading ML teams within production-scale businesses Strong understanding of LLMs, MLOps, AI platform architecture, and scalable ML systems Experience operating within high-growth SaaS, AI-native, TechBio ...

optimization and deployment (PyTorch, Torch compile, export workflows such as Torch Export and ONNX, performance profiling) Strong software engineering skills and experience building robust ML codebases Expert in Python, with additional experience in C++ or another systems language a plus Experience with GPU based training and inference, and familiarity with … performance optimization for accelerators Experience building production grade ML systems or research prototypes that have been used by others Publications, patents, or significant open‐source contributions in relevant areas are a plus 3+ years of relevant experience in machine learning, deep learning, or closely related fields Bachelor ...

that supports machine learning workflow execution and deployment. Optimise data processing systems for throughput, scalability and efficiency. Collaborate closely with Data Engineers, ML Engineers and Research teams to deliver high-quality datasets and platform capabilities. Identify and resolve bottlenecks, performance issues and system failures. Contribute to engineering best … collaboration skills. Desirable Experience Experience working within large-scale data or platform engineering environments. Exposure to machine learning infrastructure, pipelines or production ML systems. Experience supporting data processing frameworks, orchestration platforms or workflow tooling. Familiarity with JVM-based distributed systems. Experience working within highly scalable cloud or distributed ...

International Consumer Bank (ICB) Risk Modelling team is responsible for developing statistical and machine learning models to reduce fraud and credit risk within ICB. The team also engages with external vendors and supports the onboarding of vendor models, including working through Model Governance to obtain appropriate approvals … communication skills to effectively convey technical concepts and results to both technical and business audiences. Team player. Preferred Qualifications, Capabilities, and Skills Experience with ML model explainability and understanding model governance processes. Experience with model risk management frameworks. Experience with or strong interest in synthetic data generation, synthetic identity analysis ...

Machine Learning Engineer to join our Analytics division and play an important role in enhancing our metrics offering. As our first dedicated ML hire, you’ll be utilising an array of modern LLM and NLP techniques to analyse complex financial data and unlock new capabilities for our market … developers, data engineers, and product teams to productionise models into scalable, high-performance systems Requirements Confident programming skills in Python, with experience using modern ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) Good understanding of core machine learning concepts such as linear regression, reinforcement learning and deep learning ...

channelling our start‐up mentality every step of the way – meaning you'll have the opportunity to make a real impact. As a Lead Machine Learning Scientist at JPMorgan Chase within the International Consumer Bank, you will be a part of a flat‐structure organization. Your responsibilities … expected to be involved in the design and architecture of the solutions while also focusing on the entire SDLC lifecycle stages. Our Machine Learning team is at the heart of this venture, focused on getting smart ideas into the hands of our customers. We're looking for people ...

business KPIs like booking conversion and user engagement. What You’ll Do Technical Leadership & Custom Implementation: Act as the technical lead for specific ML projects within your pod. Design and implement custom model components or loss functions that don't exist "off-the-shelf," breaking down massive research goals into … production feature distribution shifts). Lead team-level post-mortems and resolve blocking corrective actions. Career Multiplier: Formally mentor mid-level and associate ML scientists, reviewing their experimental logic to ensure high scientific rigor while guiding them through applied ML and production constraints. Skills & Experience Education: Master’s or Ph.D. ...

portfolio (formerly Onfido) powers document and biometric verification, fraud detection, and identity decisions at global scale. From detecting deepfakes to enabling seamless onboarding, our ML systems sit directly on the critical path of digital trust—used by banks, fintechs, marketplaces, and enterprises worldwide. About the Team: You’ll join … working at the intersection of machine learning, product, and real-world constraints. The team is supported by a state-of-the-art ML Ops ecosystem (AWS, Encord, Ray, PyTorch Lightning, Weights & Biases) and partners closely with product and engineering to ship models into production at scale. This ...

portfolio (formerly Onfido) powers document and biometric verification, fraud detection, and identity decisions at global scale. From detecting deepfakes to enabling seamless onboarding, our ML systems sit directly on the critical path of digital trust—used by banks, fintechs, marketplaces, and enterprises worldwide. About the Team: You’ll join … working at the intersection of machine learning, product, and real-world constraints. The team is supported by a state-of-the-art ML Ops ecosystem (AWS, Encord, Ray, PyTorch Lightning, Weights & Biases) and partners closely with product and engineering to ship models into production at scale. This ...

with our hardware. Experience: Proven track record of developing novel algorithms (papers in NeurIPS, ICML, ICLR, CVPR, or Nature/Science journals) Hardware Aware ML/Neuromorphic Computing: FPGAs, ASICs, analog computing chips, spiking neural network (hardware), edge AI Unconventional training algorithms Reservoir computing, self-constrastive learning, forward-forward … learning, evolutionary algorithms, equilibrium propagation Physics informed neural networks, or applied ML to physics problems Deep understanding of mathematics, algebra/topology - key words are latent space, intrinsic dimensionality Experience working with hardware as well is a bonus ...

quarter. What You’ll Do? Design and help develop systems that serve recommendations to over 200 million users. Drive ML roadmap creation and execution, specifically around feed ranking and recall-oriented candidate generation systems. Provide technical guidance in ML model formulation, implementation, and experimentation, and take end-to-end ownership … ML systems and key user satisfaction-based metrics. Drive architectural strategy and design for complex ML systems that support the needs of users, creators, and content stakeholders. Who are you? 8+ years of professional experience in software engineering focused on deploying machine learning models in production at scale. ...

performant, reliable services. Contribute to the development and maintenance of machine learning pipelines for training, validation and deployment. Learn to use modern ML tools and platforms and apply best practices in testing, CI/CD, version control and infrastructure as code. Work in cross-functional teams alongside product … managers, engineers, and analysts. Learn from and be mentored by experienced ML Engineers and technical leaders. What we’re looking for: Some experience (academic or project-based) with Python and an understanding of machine-learning workflows and model evaluation. Interest in MLOps, model governance and responsible AI practices. ...

self-starter mindset; you proactively identify the most impactful issues and opportunities and collaboratively tackle them without being told to do so. Using advanced ML techniques to ensure Monzo’s customers money stays safe, even if their card, phone or account is compromised, sounds exciting to you. You have extensive … used in many of our backend microservices. You have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact. You thrive working on ambiguous problems and have a track record of helping your team and stakeholders resolve that ...

Active SC required We're hiring an experienced SC-cleared Data Scientist to support a high-profile central government programme delivering advanced analytics and machine-learning solutions. This role is focused on turning complex datasets into predictive insight and deployable models that directly inform policy and operational decision … understanding of machine-learning techniques (supervised, unsupervised, model evaluation) Experience with MLOps practices, including: Model versioning and deployment CI/CD for ML workflows Monitoring and performance management Experience working with cloud-based data platforms ( AWS and/or Azure ) Strong statistical knowledge and ability to explain complex ...

validity, analytical rigor, and reproducibility of outputs across the organisation Ensure strong alignment with machine learning, data engineering, and clinical teams Translate ML outputs into trial-ready products: Drive development of data science outputs that support commercial offerings and client value propositions Own the transformation of machine … outputs reinforce Qureight’s scientific credibility Represent the data science function in external scientific and commercial engagement Partner across the organisation: Work closely with ML, data engineering, clinical/translational, product, and commercial teams Align data science outputs with productization and customer needs Act as a key bridge between technical ...

Data Scientist, London/Oxford hybrid working Are you excited by the opportunity to use machine learning, NLP, and generative AI to help researchers discover knowledge faster and make better decisions? Would you enjoy turning complex scientific and business challenges into practical, production-ready AI solutions that create … strive to maintain. Our team values trust, respect, collaboration, agility, and quality. About the Role In this role, you will design and build machine learning, NLP, and generative AI solutions that support scientific discovery, knowledge extraction, decision support, and intelligent content understanding. You will work with large-scale ...

Recursion's drug discovery platform. From model training pipelines to production deployment systems, to agent infrastructure and Large Language Models, you will ensure our ML models can operate at massive scale across our supercomputing infrastructure, both on prem and in the cloud. You will work cross-functionally across ML engineering … data science, and research teams to translate requirements into robust, scalable ML infrastructure solutions. In This Role You Will: Enable AI/ML, LLM, and Agentic Systems teams for scale – The ML infrastructure team is responsible for building and operating platforms that allow data scientists and ML engineers to train ...

years, placing 4 people with them, and all 4 are still with the company. Our client is a rapidly growing AI and Machine Learning company, specialising in the research, development and deployment of advanced technology into Defence, security, intelligence and adjacent sectors. Their team includes highly experienced software … developers, data scientists, Machine Learning specialists and researchers, with strong academic, research and Defence backgrounds. They are now looking for a Senior Business Development Manager in Defence to join their senior team and help drive their next phase of growth. This is an excellent opportunity for an experienced ...

model drift or performance issues in high-throughput pipelines. Collaborate cross-functionally with Product Managers and Engineers to translate complex advertising challenges into scalable ML solutions. Embed models into low-latency systems by partnering with data scientists and engineers to ensure seamless production integration. Champion technical excellence by following best … practices for ML quality, reliability, and maintainability across the team. What You’ll Need to Thrive Our ideal candidate will bring strong expertise in some of these areas and curiosity to grow in others: Significant experience as an ML Engineer or Data Scientist, with a proven ability to write clean ...

productive environment. Nurture younger colleagues to grow their skillset and guide their professional development. The below activities in particular. Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations. Build models to predict the behaviour of physical … systems using state‐of‐the‐art machine learning and deep learning techniques. Discuss the results and implications of your work with colleagues and customers, especially how these results can address real‐world problems. Collaborate with colleagues beyond the research team to translate your models into production‐ready ...

model evaluations, helping improve accuracy and efficiency. Develop and train large‐scale generative models, pushing the boundaries of AI capabilities. Work closely with ML engineers and researchers to implement AI techniques into production workflows. Stay updated with the latest trends in AI and deep learning, contributing fresh ideas … Familiarity with MLOps tools is a plus. Strong analytical skills and ability to work in a collaborative, fast‐paced environment. What We Offer Real ML work from day one — not toy tasks, but production systems that solve actual problems. Close mentorship from engineers and researchers who’ve built and shipped ...

wide range of technical challenges across technologies to design a solution applicable to the business issue Translate business requirements into technical AI/ML features, model selection, and architecture decisions Conduct exploratory data analysis and communicate insights Collaborate with data engineers, architects, and business analysts on integrated solutions Build feature … pipelines and automated data preparation workflows Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management Develop scalable AI/ML pipelines on Databricks, Azure Machine Learning, and/or Snowflake platforms Contribute to proposals and technical assessments for new opportunities and internal knowledge ...

define project scope, interpret model results, and clearly present data-driven recommendations to both technical and non-technical audiences. Deployment & MLOps: Collaborate with ML/Data Engineers to deploy, monitor, and maintain ML models in a production environment, ensuring stability and performance over time. Required Skills and Qualifications Technical Expertise … Expert proficiency in Python and its core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/ ...